code: def __init__(
      self, n_past=4, n_future=1, RFparams={"n_estimators": 250}
  ):
      self.n_past = n_past
      self.n_future = n_future
      self.model = RandomForestRegressor(**RFparams)
  
file_path: AIX360/tests/tssaliency/test_tssaliency.py
imports: import os
  import unittest
  import numpy
  import pandas
  from sklearn.model_selection import train_test_split
  from sklearn.ensemble import RandomForestRegressor
  from aix360.algorithms.tsutils.tsframe import tsFrame
  from aix360.datasets import SunspotDataset
  from aix360.algorithms.tssaliency import TSSaliencyExplainer
label_desc: Use image node_id 1 to create a new RandomForestUniVariateForecaster object  with example: obj = RandomForestUniVariateForecaster(n_past, n_future, RFparams)